Developing a Predictive Model for CBR Value Using Soil Index Properties: A Case Study of the Mekelle Asphalt Road Project

Abstract

California Bearing Ration (CBR) value is an important soil parameter considered as main design input in the design of flexible pavements and runways of airfields. The design of pavement thickness determined depending on the strength and stability of sub-grade materials are evaluated before construction of pavement by using CBR test. And Index properties of soil are properties which are used to characterize soils and facilitate identification and classification of soils for engineering purposes. However, in a large-scale road project soil properties vary from region to region and season to season as it appears naturally. Thus, developing empirical equations specific to a certain region and soil type could be considered nearly as good insight of soil behavior. This study was conducted to developing a predictive model for CBR value using soil index properties of soils in the case study of the Mekelle Asphalt Road Project. The study was carried out using 27 samples collected from SUR Construction PLC Mekelle Asphalt Road Project. And test procedures were carried out based on the (ASTM) and (AASHTO) at Mekelle Asphalt Road Project Laboratory. This study tries to use a single linear regression model and multiple linear regression models to characterize the strength of the subgrade soils from the soil index properties using a statistical method. The laboratory test results and statistical analysis were carried out using Microsoft Excel and SPSS software. To develop the intended correlation and regression analysis CBR value at different blows such as 10, 30 and 65 blows were considered as dependent variable. And index properties of soil such as percent passing 2.0, 0.425, and 0.075 mm (sieve No. 10, 40, and 200) sieve size, LL, PI, OMC and DD at points 10, 30, 65 blows were considered as independent variables. From the regression analysis result, the equation and coefficient of determination developed are:  CBRat 10 Blow = -7.99 - 0.024LL - 0.025PI + 0.187P10 - 0.133P40 + 0.027P200 - 0.025OMC + 2.68DDat 10 blow, R2=0.913, adj R2=0.881  CBRat 30 Blows = -3.1 - 0.058LL + 0.006PI + 0.133P10 - 0.092P40 + 0.008P200 - 0.055OMC + 2.87DDat 30 Blows, R2=0.965, adj R2=0.953  CBRat 65 Blows = -3.301 - 0.113LL + 0.054PI + 0.085P10 - 0.004P40 + 0.050P200 - 0.088OMC + 1.373DDat 65 Blows, R2=0.928, adj R2=0.902